The present invention relates to fingerprint/palmprint image processing system, method and program, for use in fingerprint collation, fingerprint classification and palmprint collation, etc.
In the prior art, a method for automatically extracting a ridge line information such as a ridge line direction and a ridge line pitch from an fingerprint/palmprint image includes, for example, a “Ridge Line Direction Pattern Smoothing Method and System” described in Japanese Patent No.2,765,335, and “Classification of Fingerprint Patterns by Relaxation Method”, the 22nd National Convention (1981 First Term Session), Information Processing Society of Japan by Kawakoshi et. al.
The “Ridge Line Direction Pattern Smoothing Method and System” describes a technique based on the theory of minimizing energy. An evaluation function is assigned for an extracted direction for each two-dimensional local region of an image with a scale of reliability. By minimizing the evaluation function, the ridge line pattern is smoothened. On the other hand, in the “Classification of Fingerprint Patterns by Relaxation Method,” information of directions extracted for each two-dimensional local region of an image is smoothened by a so-called relaxation method.
In the method described in Japanese Patent No.2,765,335, however, if it is intended to smoothen an image including a wrinkle, circumferential regions are smoothened in line the wrinkle, and it is in some cases that the wrinkle is rather emphasized, On the other hand, in the technology described for the classification of the fingerprint pattern by the relaxation method, although the relaxation method is used as the technique for smoothening information of direction extracted for each local region, the smoothening is carried out in line with the wrinkle for the part of existing wrinkles which also frequently exist in palmprint and which are parallel to each other at a similar pitch and extent over a large area, with the result that the wrinkles are emphasized.
The inventor of the present application proposes in Japanese Patent Application Pre-examination Publication JP-A-09-167230 (which corresponds to U.S. Pat. No. 5,937,082, the content of which is incorporated by reference in its entirety into this application) a fingerprint/palmprint image processor capable of extracting a ridge line image from a fingerprint/palmprint image without receiving the effect of the wrinkle. In this fingerprint/palmprint image processor, an inputted fingerprint or palmprint image is divided into a plurality of blocks, and a plurality of bridge line candidates are detected for each block, and the candidate which can be considered to be surely a ridge line is determined from the detected ridge line candidates in one block, and in the other blocks, ridge line candidates having the consistency with the determined ridge line candidate are chosen. The ridge line spatially continues as a ridge line, and the wrinkle spatially continues as a wrinkle, but, generally, the wrinkle does not continue to the ridge line. Therefore, if a candidate which can be considered to be surely a ridge line is detected, and if a candidate having the continuity with the detected candidate is chosen from other local candidates, it is possible to correctly detect the ridge line in a region including many wrinkles.
FIG. 10 is a block diagram illustrating the fingerprint/palmprint image processor mentioned above. The block diagram of FIG. 10 corresponds to FIG. 9 of JP-A-09-167230, but is one obtained by simplifying FIG. 9 of JP-A-09-167230 in order to simplify the following description. In FIG. 10, the reference number 11 designates an image input means, and the reference number 12 indicates a local information extracting means. The reference number 13 denotes a highly reliable region determining means, and the reference number 14 shows an adjacent region group detecting means. The reference number 15 designates a ridge line candidate selecting means, and the reference number 16 indicates an image generation means. Here, the highly reliable region determining means 13 corresponds to the first ridge line candidate image selecting portion 12, the connectivity evaluating portion 13, the clustering portion 14, and the cluster evaluating portion 15 shown in FIG. 9 of JP-A-09-167230. The adjacent region group detecting means 14 and the ridge line candidate selecting means 15 correspond to the optimum ridge line candidate image selecting portion 17 shown in FIG. 9 of JP-A-09-167230.
FIG. 11 is a flowchart illustrating an operation of the system shown in FIG. 10. In FIG. 11, the image input means 11 reads fingerprint or palmprint as an image, and supplies the image in the form of a digital image to the local information extracting means 12 (S1001). The local information extracting means 12 divides the received original image into two-dimensional local regions (S1002), and extracts from each local region a plurality of images (which will be called a “ridge line candidate image”) as a candidate which expresses a ridge line existing in that local region (S1003). The ridge line candidate images are numbered.
The ridge line candidate images thus extracted is supplied to the highly reliable region determining means 13, the ridge line candidate selecting means 15 and the image generation means 16. In the highly reliable region determining means 13, a ridge line candidate which can be considered to be surely a ridge line is detected and a local region including that ridge line candidate (highly reliable region), are determined from the plurality of ridge line candidate images (S1004), and supplied to the adjacent region group detecting means 14, the ridge line candidate selecting means 15 and the image generation means 16.
The adjacent region group detecting means 14 finds all local regions (adjacent region) which adjoin the highly reliable region (S 1005). For example, if it is assumed that the highly reliable regions (regions shown in the dense hatching in FIG. 12-(a)) were detected, regions (regions shown in the dilute hatching in FIG. 12-(a)) which adjoins the highly reliable regions are detected as a adjacent region. Next, whether or not one or more adjacent regions are detected, is discriminated (S1006). For example, in the example shown in FIG. 12-(a), since one or more adjacent regions exist, the processing goes into a step S1007 in which, in each of all the adjacent regions detected, a ridge line image is selected from the ridge line candidate images by the ridge line candidate selecting means 15, and the number of the selected ridge line candidate image is notified to the image generation means 16.
For example, in order to perform the ridge line candidate image selection for the adjacent region “A” shown in FIG. 12-(a), a candidate having a high level of continuity is selected from ridge line candidate images “1” to “6”. In this example, the ridge line candidate image “2” is selected.
Thereafter, the processing returns to the step S705. In the highly reliable region or the local region for which the selection of the ridge line candidate image has been completed, all adjacent regions which are neither the highly reliable region nor the local region for which the selection of the ridge line candidate image has been completed, are selected. Namely, in the example shown in FIG. 12-(a), all regions downward adjacent to the adjacent region already detected are found out. Then, in the step S 1006, whether or not one or more adjacent regions are detected, is discriminated. If one or more adjacent regions exist, the processing does to the step S1007, in which, in each of all the adjacent regions, a ridge line image is selected from the ridge line candidate images. In the following, the steps S1005 to S1007 are repeated, and when it is discriminated to be “NO” in the step S1006, since the processing has been completed for all the local regions, the image generation means 16 restores a whole ridge line image by using the selected ridge line candidate images, as shown in FIG. 12-(b) (S1008).
The fingerprint/palmprint image processor mentioned above, disclosed in JP-A-09-167230, can extract the ridge line without being influenced by wrinkles. However, since the ridge line image is determined for each local region by importantly considering the continuity between adjacent regions, another disadvantage is encountered in which, in a ridge line having a large curvature such as a core shown in FIG. 13-(a) and a delta shown in FIG. 13-(b), even if the ridge lines were clear, a candidate image having a wrinkle having a good continuity other than the ridge line is selected, with the result that it fails to extract the ridge line.